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Now showing items 1 - 16 of 45

  • Epidemiology of acute kidney injury in hospitalized pregnant women in China

    Liu, Diankun   He, Wenjuan   Li, Yanqin   Xiong, Mengqi   Wang, Long   Huang, Jingxin   Jia, Ling   Yuan, Shuling   Nie, Sheng  

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  • A revised progressive TIN densification for filtering airborne LiDAR data

    Nie, Sheng   Wang, Cheng   Dong, Pinliang   Xi, Xiaohuan   Luo, Shezhou   Qin, Haiming  

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  • miR-495 Mediates Metabolic Shift in Glioma Cells via Targeting Glut1

    Nie, Sheng   Li, Keqin   Huang, Yi   Hu, Qinle   Gao, Xiang   Jie, Sun  

    Cancer cell metabolism is often characterized by a shift from an oxidative to a glycolytic bioenergetics pathway, a phenomenon known as the Warburg effect. Whether the deregulation of microRNAs contributes to the Warburg effect remains largely unknown. Here, we show that miR-495 expression is decreased and thus induces a metabolic shift in glioma cells. miR-495 performs this function by increasing the expression of Glut1, leading to the increase of glucose uptake and lactate production. The altered metabolism induced by miR-495 results in the rapid growth of cancer cells. These results identify miR-495 as a molecular switch involved in the orchestration of the Warburg effect in glioma cells via targeting the expression of Glut1.
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  • Estimating leaf area index of maize using airborne full-waveform lidar data

    Nie, Sheng   Wang, Cheng   Dong, Pinliang   Xi, Xiaohuan  

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  • Estimating Leaf Area Index of Maize Using Airborne Discrete-Return LiDAR Data

    Nie, Sheng   Wang, Cheng   Dong, Pinliang   Xi, Xiaohuan   Luo, Shezhou   Zhou, Hangyu  

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  • Estimating the height of wetland vegetation using airborne discrete-return LiDAR data

    Nie, Sheng   Wang, Cheng   Xi, Xiaohuan   Luo, Shezhou   Li, Shihua   Tian, Jianlin  

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  • Signal-to-noise ratio–based quality assessment method for ICESat/GLAS waveform data

    Nie, Sheng   Wang, Cheng   Li, Guicai   Pan, Feifei   Xi, Xiaohuan   Luo, Shezhou  

    Data quality determines the accuracy of results associated with remote sensing data processing and applications. However, few effective studies have been carried out on quality assessment methods for the full-waveform light detecting and ranging data. Using the geoscience laser altimeter system (GLAS) waveform data as an example, a signal-to-noise ratio (SNR)-based waveform quality assessment method is proposed to analyze the relationship between the SNR and its controlling factors, i.e., laser type, laser using time, topographic relief, and land cover type, and study the impacts of these factors on the quality of the GLAS waveform data. Results show that the SNR-based data quality assessment method can quantitatively and effectively assess the GLAS waveform data quality. The SNR linearly attenuates with the laser using time, and the attenuation rate varies with laser type. The topographic relief is inversely correlated with the SNR of the GLAS data. As the land cover structure (especially the vertical structure) becomes more complex, the SNR of the GLAS data decreases. It was found that land cover types in descending order of the SNR values are desert, farmland, water body, grassland, city, and forest. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
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  • A revised terrain correction method for forest canopy height estimation using ICESat/GLAS data

    Nie, Sheng   Wang, Cheng   Zeng, Hongcheng   Xi, Xiaohuan   Xia, Shaobo  

    Abstract Although spaceborne Geoscience Laser Altimeter System (GLAS) can measure forest canopy height directly, the measurement accuracy is often affected by footprint size, shape and orientation, and terrain slope. Previous terrain correction methods only took into account the effect of terrain slope and footprint size when estimating forest canopy height. In this study, an improved terrain correction method was proposed to remove the effect of all aforementioned factors when estimating canopy height over sloped terrains. The revised method was found significantly better than the traditional ones according to the canopy height tested using small footprint LiDAR data in China. It reduced the RMSE of the canopy height estimates by up to 1.2 m. The effect of slope on canopy height estimation is almost eliminated by the proposed method since the slope had little correlation with the canopy heights estimated by revised method. When the footprint eccentricity is small, the canopy height error due to the footprint shape and orientation is small. However, when the footprint eccentricity is large enough, the height estimation error due to footprint shape and orientation is large. Therefore, it is necessary to take into account the influence of footprint shape and orientation on forest canopy estimation.
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  • Vegetation Horizontal Occlusion Index (VHOI) from TLS and UAV Image to Better Measure Mangrove LAI

    Guo, Xianxian   Wang, Le   Tian, Jinyan   Yin, Dameng   Shi, Chen   Nie, Sheng  

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  • A Ground Elevation and Vegetation Height Retrieval Algorithm Using Micro-Pulse Photon-Counting Lidar Data

    Zhu, Xiaoxiao   Nie, Sheng   Wang, Cheng   Xi, Xiaohuan   Hu, Zhenyue  

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  • Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest

    Nie, Sheng   Wang, Cheng   Zeng, Hongcheng   Xi, Xiaohuan   Li, Guicai  

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  • Retrieving leaf area index in discontinuous forest using ICESat/GLAS full-waveform data based on gap fraction model

    Yang, Xuebo   Wang, Cheng   Pan, Feifei   Nie, Sheng   Xi, Xiaohuan   Luo, Shezhou  

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  • Combining hyperspectral imagery and LiDAR pseudo-waveform for predicting crop LAI, canopy height and above-ground biomass

    Luo, Shezhou   Wang, Cheng   Xi, Xiaohuan   Nie, Sheng   Fan, Xieyu   Chen, Hanyue   Yang, Xuebo   Peng, Dailiang   Lin, Yi   Zhou, Guoqing  

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  • Epidemiology and outcomes of acute kidney injury in hospitalized cancer patients in China

    Cheng, Yichun   Nie, Sheng   Li, Lu   Li, Yanqin   Liu, Diankun   Xiong, Mengqi   Wang, Long   Ge, Shuwang   Xu, Gang  

    Acute kidney injury (AKI) is a common complication in cancer patients, but the data are lacking in Asian countries. We aimed to assed the epidemiology, correlated risk factors and outcomes of AKI in cancer patients from China. We conducted a nationwide cohort study of cancer patients who were admitted to 25 general and children hospitals across China from January 1, 2013 to December 31, 2015. We obtained patient-level data from the electronic hospitalization information system and laboratory databases of all inpatients who had at least two serum creatinine tests within any 7-day window during their first 30 days of hospitalization. AKI was defined and staged according to Kidney Disease Improving Global Outcomes criteria. Incidence rate and risk factor profiles for AKI were examined. Outcomes of interest included in-hospital mortality, length of stay and daily costs. A total of 136,756 adult cancer patients were assessed in our study. The overall incidence of AKI was 7.5%, of which 1.6% were community acquired and 5.9% hospital acquired. The top three cancer types with high incidence of AKI were bladder cancer, leukemia, and lymphoma. Risk factors for community-acquired and hospital-acquired AKI were similar, including age, increased baseline serum creatinine, shock and urinary tract obstruction. In-hospital death occurred in 12.0% with AKI vs. 0.9% cancer patients without AKI. After adjustment for confounders, the severe AKI was associated with higher risk of in-hospital death, prolonged length of stay and higher daily costs. Clinicians should increase their awareness of AKI in hospitalized cancer patients. What's new? Acute kidney injury is a significant cause of morbidity and mortality in cancer patients. In China, however, little is known about its occurrence, despite the country's steep rise in cancer incidence. Here, the authors analyzed data on acute kidney injury in cancer patients admitted to general hospitals in China between 2013 and 2015. Analyses show that acute kidney injury affected about 7.5 percent of the 136,756 adult cancer patients included in the study. Incidence was highest in bladder cancer, leukemia, and lymphoma patients. In severe cases, patients experienced significantly elevated risks of in-hospital death and extended hospitalization.
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  • Development of spectral-phenological features for deep learning to understand Spartina alterniflora invasion

    Tian, Jinyan   Wang, Le   Yin, Dameng   Li, Xiaojuan   Diao, Chunyuan   Gong, Huili   Shi, Chen   Menenti, Massimo   Ge, Yong   Nie, Sheng   Ou, Yang   Song, Xiaonan   Liu, Xiaomeng  

    Invasive Spartina alterniflora (S. alterniflora), a native riparian species in the U.S. Gulf of Mexico, has led to serious degradation to the ecosystem and biodiversity as well as economic losses since it was introduced to China in 1979. Although multi-temporal remote sensing offers unique capability to monitor S. alterniflora over large areas and long time periods, three major hurdle exist: (1) in the coastal zone where S. alterniflora occupies, frequent cloud coverage reduces the number of available images that can be used; (2) prominent spectral variations exist within the S. alterniflora due to phonological variations; (3) poor spectral separability between S. alterniflora and its co-dominant native species is often presented in the territories where S. alterniflora intruded in. To articulate these questions, we proposed a new pixel-based phenological feature composite method (PpfCM) based on Google Earth Engine. The Ppf-CM method was brainstormed to battle the aforementioned three hurdles as the basic unit for extracting phonological feature is individual pixel in lieu of an entire image scene. With the Ppf-CM-derived phenological feature as inputs, we took a step further to investigate the performance of the latest deep learning method as opposed to that of the conventional support vector machine (SVM); Lastly, we strive to understand how S. alterniflora has changed its spatial distribution in the Beibu Gulf of China from 1995 to 2017. As a result, we found (1) the developed Ppf-CM method can mitigate the phonological variation and augment the spectral separability between S. alterniflora and the background species regardless of the significant cloud coverage in the study area; (2) deep learning, compared to SVM, presented better potentials for incorporating the new phenological features generated from the Ppf-CM method; and (3) for the first time, we discovered a S. alterniflora invasion outbreak occurred during 1996-2001.
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  • Methylation of the CDKN2A Gene Increases the Risk of Brain Arteriovenous Malformations

    Chen, Xiaosheng   Liu, Yuchun   Zhou, Shengjun   Nie, Sheng   Lin, Zhiqin   Zhou, Chenhui   Sun, Jie   Gao, Xiang   Huang, Yi  

    Brain arteriovenous malformations (BAVMs) and intracranial aneurysms (IAs) are the results of a combination of genetic and environmental factors. Epigenetic factors also play an important role in the pathogenesis of these disorders. The aim of this study was to determine the effect of DNA methylation at the cyclin-dependent kinase inhibitor 2A (CDKN2A) gene on the risk of BAVMs and IAs. A total of 70 intracranial vascular malformation patients (22 patients with BAVMs and 48 patients with IAs) and 26 patients with cerebral trauma (used as controls) were included in this study. DNA methylation levels of eight cytosine-phosphate-guanine (CpG) dinucleotides present in the CDKN2A gene were measured using bisulfite pyrosequencing technology. Significant differences in methylation at CpG1 (p =3D 0.005), CpG5 (p =3D 0.011), and CpG8 (p =3D 0.017) were observed between BAVM patients and controls. CDKN2A methylation levels in BAVM patients were much higher than those in IA patients (CpG5: p =3D 0.004; CpG8: p =3D 0.010). Significant differences were observed between female IA patients and female BAVM patients (CpG5: p =3D 0.006; CpG8: p =3D 0.005; mean: p =3D 0.015). Receiver operating characteristic (ROC) curve analysis showed that the CDKN2A gene methylation trended toward a diagnostic indicator in BAVM patients (area under curve =3D 0.711, p =3D 0.013). In conclusion, our study demonstrated that the CDKN2A gene methylation levels are significantly correlated with the occurrence of BAVMs, and thus, have potential for use in the early diagnosis of BAVMs. Future research on the pathogenesis of BAVMs should focus on the role of genetic factors in aberrant venous development. The association of the CDKN2A gene with venous development also deserves further study.
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